The Nature and Nurture of Generosity: What can we learn from behavioral genetics?

René Bekkers

Center for Philanthropic Studies VU University Amsterdam

WIMPS, November 18, 2014

Thanks

• • • To the McArthur Foundation for funding the MIDUS data collection.

Colleagues who gave feedback: Dorret Boomsma, Dinand Webbink, Sara Konrath, Paul van Lange, Daniëlle Posthuma.

To be submitted as a chapter for a CESifo volume published at MIT Press.

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Three questions

• • • How alike are twins in the United States with respect to prosocial behavior?

Are differences among twins in giving and volunteering related to differences in education and religion?

If so, what explains these relationships?

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Prosocial behavior Formal: philanthropy Informal: helping

Money Time Social support

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Care

7

250 200 150 100 50 0 other natural sciences education and health public administration marketing & communication philanthropic studies economics sociology psychology

Number of publications per year about philanthropy by academic discipline (1899-2009)

Source: Bekkers & Dursun (2013), based on Bekkers & Wiepking (2011). ‘A Literature Review of Empirical Studies of Philanthropy: Eight Mechanisms that Drive Charitable Giving’. Nonprofit and Voluntary Sector Quarterly, 40(5): 924-973. Available at www.understandingphilanthropy.com

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Ubiquitous correlates of philanthropy

1. Religion: – Affiliation (yes>no) – Denomination (Protestant>Catholic) – Participation (church attendance) 2. Education: – Level achieved

The variance between fields of study is small

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Where do the correlations originate?

The more general research questions: 1. Why are religion and education correlated with prosocial behavior?

2. To what extent are these relationships the result of environmental influences?

3. Are these relationships causal?

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Selection and causation

Behavior Education IQ, Other factors November 18, 2014 WIMPS, IUPUI 11

All selection, no causation

Behavior Education IQ, Other factors November 18, 2014 WIMPS, IUPUI 12

Selection and Causation

About 60%?

Education Factors X 1…n IQ, parental income, social science classes, college plans, extraversion, openness to experience Participation Bekkers, R. & Ruiter, S. (2008). ‘Education and voluntary association participation: Evidence for selection and causation’. Paper presented at the 103d ASA Annual Meeting, Boston, August 2, 2008.

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Selection, causation, mediation

Mediating variable Education Behavior IQ, other factors November 18, 2014 Another mediating variable WIMPS, IUPUI 14

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Three ‘theories’ on philanthropy

Philanthropy varies between social groups 1. because the resources of group members vary; 2. because the social values of groups vary; 3. because members of different groups have different self-identities.

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The ideal experiment would randomize education

November 18, 2014 VWO = higher secondary education (≤ gymnasium) VMBO = lower vocational education WIMPS, IUPUI 18

Monozygotic twins

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The unique environmental influence of education

Note that shared environmental influences are also excluded by design in this analysis November 18, 2014 WIMPS, IUPUI 20

A

What behavioral geneticists do: the ACE model

Additive genetic effects Typically 40-60% C Common (shared) environmental effects E Unique (non-shared) environmental effects (including error) Typically less than 10% (often zero) Typically 30-50% November 18, 2014 WIMPS, IUPUI 21

Note

• The first law of behavior genetics, as formulated by Eric Turkheimer (2000): “All human behavioral traits are heritable” • Eva Krapohl in a recent interview in The

Atlantic :

“Heritability describes what is; it does not predict what could be” November 18, 2014 WIMPS, IUPUI 22

A

ACE mediated effects model

Religiousness C Prosocial behavior E Total effect on prosocial behavior

A

10.2

C

27.6

Mediated by religiousness 7.5 (73.5%) 13.6

(49.3%) Koenig et al., 2007; n= 165 MZ and 100 DZ twin pairs November 18, 2014 WIMPS, IUPUI

E

62.3

2.9

(4.7%) 23

Biometric model fitting

• • • • • Fit statistics of various biometric models are compared to identify the best-fitting model.

Models depend on assumptions such as the Equal Environments Assumption.

The EEA is often disputed theoretically.

Empirical tests show it is often violated.

The resulting bias, however, seems to be minor (see Felson, Soc.Sc.Res., 2014).

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What molecular geneticists do

• • • Genome Wide Association Studies (GWAS): identify ‘candidate genes’ that could explain variance in some outcome variable.

Typically, individual genes like OXTR and DRD4 explain tiny fractions of variance (<1%).

Typically, all single nucleotide polymorphisms (SNPs) combined explain less variance (16% of education) than estimated in biometric models (35%) – ‘missing heritability’ problem.

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Where is the social science?

• • • • • In the variance explained by shared and unique environmental factors.

Let us rule out genetic effects by looking at monozygotic twins only. Any difference between MZ twins must have roots in the unique environment.

This choice avoids problems with the EEA.

Note that MZ twins also share 100% of shared environmental effects.

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The problem

• “…families whose unobservable characteristics cause them to have a high likelihood of volunteering are also more likely to educate their children, so the relationship between schooling and volunteering is just a correlation caused by an excluded common cause.” John Gibson (2001) November 18, 2014 WIMPS, IUPUI 27

This is not my idea

• • • In 2001, New Zealand economist John Gibson published a study of volunteering among 85 identical twin pairs.

Though education in the pooled sample is associated with more volunteering, pairwise comparisons reveal the opposite. The twin with more years of education was found to volunteer fewer hours.

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The implication

• • • Genetic effects cause a positive association between education and volunteering.

Unique environmental effects of education on volunteering are negative in this sample.

One interpretation of the negative effect is that it is the result of the opportunity cost of volunteering, potentially amplified by a decision making process within the household.

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Related literature

• The twin fixed effects model has been used in economics to estimate the influence of schooling on income since the 1970s (Behrman & Taubman, 1976; Ashenfelter & Kreuger, 1994; Ashenfelter & Rouse, 1998; Isacsson, 1999; Miller, Mulvey & Martin, 1995; Bonjour et al., 2003).

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E

Environment mediation model

Religiousness Prosocial behavior Education Note that this is a unique environment mediation model November 18, 2014 WIMPS, IUPUI 31

The MIDUS data

• • • Two wave longitudinal panel survey on Midlife in the United States (1995 and 2005) sponsored by the McArthur Foundation.

The RDD sample selection procedure included twin screening questions.

Only English-speaking respondents aged 25-74 living in the US who were physically and mentally able to complete the interview were allowed to participate.

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Assessing zygosity

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Are twins different at all?

MZ DZ Yes – here’s the discordance table:

Education

55% 64%

Religious affiliation

50% 53% Proportions of respondents from the same twin pair not reporting exactly the same level of education and religious affiliation November 18, 2014 WIMPS, IUPUI 34

ACE model results

Education Strength of religiosity Frequency of church attendance Amount donated ($) Hours volunteered Financial assistance to friends / family Hours helping friends / family

A

29.8

22.8

33.7

15.8

17.7

26.6

C

38.6

32.7

46.7

E

31.5

39.3

53.3

66.3

84.2

82.3

73.5

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ACE model for volunteer hours

84,2 November 18, 2014 WIMPS, IUPUI A C E 36

ACE model for volunteer hours

84,2 November 18, 2014 WIMPS, IUPUI A C E 37

ACE model for volunteer hours

84,2 November 18, 2014 WIMPS, IUPUI A C E 38

ACE model for volunteer hours

15,8 A C E November 18, 2014 WIMPS, IUPUI 39

ACE model for volunteer hours

15,8 A C E November 18, 2014 WIMPS, IUPUI 40

ACE model for volunteer hours

15,8 A C E 41 November 18, 2014 WIMPS, IUPUI

Remember

• •

“Heritability describes what is; it does not predict what could be”.

These are the results of educational careers and systems for those in midlife in the US.

“All human behavioral traits are heritable”.

25% is not much compared to 75% for IQ.

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The higher educated give more

These differences are massive: amounts donated in the top category are nine times the amount donated in the lowest category November 18, 2014 WIMPS, IUPUI 43

The higher educated volunteer more

November 18, 2014 Again, large differences WIMPS, IUPUI 44

Informal prosocial behaviors

November 18, 2014 WIMPS, IUPUI Perhaps Americans with less education know more people in need of support?

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The religious give more

November 18, 2014 Religious giving is included in this figure. Excluding donations to religion, the differences are much smaller.

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The religious volunteer more

This figure includes volunteering for religious organizations.

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Informal prosocial behaviors

Perhaps Americans who attend church less often know more people in need of financial assistance and support?

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Two basic regression models

1. Between effects model: ignores the twin pair structure, replicates bivariate analyses. Includes genetic + environmental effects.

2. Within MZ twin fixed effects model: does the higher educated / more religious twin of an MZ pair give and volunteer more than the less educated / religious co-twin? Includes environmental effects only.

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Educational gradients among MZ twins

0,40 0,30 0,20 0,10 0,00 -0,10 -0,20 -0,30 Giving high school or less Non-religious giving some college more than some college Volunteering Non-religious volunteering November 18, 2014 WIMPS, IUPUI 50

Giving by co-twin

0,40 0,30 0,20 0,10 0,00 -0,10 -0,20 -0,30 1 2 3 1. high school or less 1 2 2. some college 3

Co-twin education x R education

1 2 3 3. more than some college November 18, 2014 WIMPS, IUPUI MZ DZ 51

Education and giving

400 350 300 250 200 150 100 50 0 *** Between siblings, DZ twins, and MZ twins November 18, 2014 *** FE DZ twins *** p <.001

FE MZ twins WIMPS, IUPUI 52

Two further models

• • Reduced form within MZ twin model: excludes religious denomination dummies, retaining education, church attendance and strength of religiosity.

Mediated reduced form within MZ twin model: adds social responsibility, prosocial self-identity, household income, and assets.

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Education and giving among MZs

180 160 140 120 100 80 60 40 20 0 *** *** Between Within Reduced within Mediated reduced within November 18, 2014 WIMPS, IUPUI Total amount donated excluding religion *** p <.001

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Education estimates on total giving

250 200 150 100 50 0 Between November 18, 2014 Within Reduced within Mediated reduced within WIMPS, IUPUI -1SE Estimate +1SE 55

Education and volunteering

0 -2 -4 -6 -8 -10 10 8 6 4 2 *** November 18, 2014 *** Between Within Reduced within Mediated reduced within WIMPS, IUPUI hours volunteered excluding religious *** p <.001

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200

Resources and volunteering

* * ** ** 150 * 100 College Wages *$100 Assets *$1k 50 0 -50 Between Sibs Between Between Sibs Between Sibs Between Sibs *** p <.001

** p <.01

* p <.05

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Resources and volunteering

200 150 100 50 *** *** *** *** *** 0 -50 Between MZ Between Between MZ ** Between MZ Between MZ *** p <.001

** p <.01

* p <.05

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Resources and volunteering

100 80 60 *** *** *** * * 40 20 0 -20 -40 Between MZ Between MZ Between MZ Between MZ Between MZ *** p <.001

** p <.01

* p <.05

College Wages *$100 Assets *$1k November 18, 2014 WIMPS, IUPUI 59

Resources and volunteering

100 80 60 40 20 0 -20 -40 Fixed MZ Fixed MZ Fixed MZ Fixed MZ Fixed MZ *** p <.001

** p <.01

* p <.05

College Wages *$100 Assets *$1k November 18, 2014 WIMPS, IUPUI 60

Church attendance and giving

25 20 15 10 5 0 *** Between *** Within *** *** Amount excluding religion Reduced within Mediated reduced within WIMPS, IUPUI *** p <.001

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Church attendance and volunteering

0 -0,2 -0,4 -0,6 -0,8 -1 0,8 1 0,6 0,4 0,2 Between November 18, 2014 Within Reduced within Mediated reduced within WIMPS, IUPUI hours volunteered excluding religious 62

Strength of religiosity and giving

300 250 200 150 100 50 0 -50 -100 Between November 18, 2014 * * WIMPS, IUPUI * Amount excluding religion Within Reduced within Mediated reduced within * p <.05

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Religiosity and volunteering

15 10 5 0 40 35 30 25 20 ** ** Between *** *** Within *** *** *** Reduced within Mediated reduced within WIMPS, IUPUI hours volunteered excluding religious *** p <.001; ** p < .01

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Conclusions

• • • The association between the level of education and giving and volunteering is due to genetic or shared environmental effects.

The association between religiosity and charitable giving is due to unique environmental effects, but it is limited to church contributions.

Religiosity nurtures volunteering, also beyond religious organizations.

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Mediation

• • • • Education hardly mediates unique environmental influences on giving (-0.5%) or volunteering (1.8%).

Religion mediates unique environmental influences on giving (15.6%) but not on volunteering (2.0%).

Education effects are partly mediated (25%) by income and assets.

Religiosity effects are mediated by prosocial self-identity (55%), but not by prosocial values.

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Or vice versa

• • • • Perhaps volunteering nurtures religiosity.

Or perhaps an omitted (shared?) environmental effect nurtures volunteering and religiosity.

We cannot infer causality from the twin fixed effects model.

But we can look at changes in religiosity and volunteering between the two waves.

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…and?

• • Respondents who quit volunteering between the first and the second wave are less frequently attending church and report lower strength of religiosity in the second wave than in the first wave.

Respondents who started volunteering are more frequently attending church in the second wave. November 18, 2014 WIMPS, IUPUI 70

The measurement error problem

• • Could differential measurement error explain the pattern of results?

That is unlikely. The test-retest correlation of education is higher (.87) than that of the frequency of church attendance (.72). It is similar to strength of religiosity (.84).

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The variance problem

• • Could a differential lack of variance explain the pattern of results?

That is unlikely. MZ twins are more likely to be discordant with respect to education (55%) than with respect to religion (50%).

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Future directions

• • Replicate this finding using data from other samples of twins, in the US and beyond.

Examine other dependent variables using this method: trust, subjective well being, prosocial values...

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Schooling effects on income

5 0 -5 35 30 25 20 15 10 *** November 18, 2014 *** Between *** *** Siblings FE *** *** DZ FE WIMPS, IUPUI Education (12 cat) College+ MZ FE *** p <.001

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René Bekkers

Center for Philanthropic Studies VU University Amsterdam [email protected]

Blog: http://renebekkers.wordpress.com

Twitter: @renebekkers

References

• • • • • Bekkers, R. & Dursun, E. (2013). “A Brief History of Research on Philanthropy.” http://www.understandingphilanthropy.com

Felson, J. (2014). “What can we learn from twin studies? A comprehensive evaluation of the equal environments assumption.” Social Science Research, 43: 184-199.

Gibson, J. (2001). “Unobservable Family Effects and the Apparent External Benefits of Education.” Economics of Education Review, 20: 225-233.

Koenig, L.B., McGue, M., Krueger, R.F., Bouchard, T.J. (2007). “Religiousness, Antisocial Behavior, and Altruism: Genetic and Environmental Mediation.” Journal of Personality, 75: 265-290. Reuter, M., Felten, A., Penz, S., Mainzer, A., Markett, S. & Montag, C. (2013). “The influence of dopaminergic gene variants on decision making in the ultimatum game.” Frontiers in Human Neuroscience, 7: 1-8.

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More references

• • • • • • • Ashenfelter, O., & Krueger, A. (1994). “Estimates of the economic return to schooling from a new sample of twins.” American Economic Review, 84, 1157–1173.

Ashenfelter, O., & Rouse, C. (1998). “Income, schooling and ability: Evidence from a new sample of identical twins.” Quarterly Journal of Economics, 113, 153–284. Behrman, J. & Taubman, P. (1976). “Intergenerational Transmission of Income and Wealth.” American Economic Review, 66: 436-440.

Behrman, J. & Rosenzweig, M.R. (1999). “Ability biases in schooling returns and twins: a test and new estimates.” Economics of Education Review, 18: 159-167.

Bonjour, D., Cherkas, L., Haskel, J., Hawkes, D., & Spector, T. (2003). “Returns to Education: Evidence from UK Twins.” American Economic Review, 93: 1799-1812.

Isacsson, G. (1999). “Estimates of the Return to Schooling in Sweden from a Large Sample of Twins.” Labour Economics, 6: 471-489.

Miller, P., Mulvey, C. & Martin, N. (1995). “What Do Twins Studies Reveal About the Economic Returns to Education? A Comparison of Australian and U.S. Findings." American Economic Review, 85: 586-599.

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Measures

Donations. Donations to organizations were measured with the following question: “On average, about how many dollars per month do you or your family living with you contribute to each of the following people or organizations? If you contribute food, clothing, or other goods, include their dollar value. (If none, enter "0".)” After this introduction, donations to three categories of organizations were measured: (1) to religious groups; (2) to political organizations or causes; (3) to any other organizations, causes, or charities (including donations made through monthly payroll deductions)? Amounts donated per month were multiplied by 12 to obtain the total amount donated per year. The sum of these contributions is the variable for the total amount donated to organizations. A separate variable was created excluding donations to religion to see if the relationship between religion and philanthropy would also hold for ‘secular giving’. The test-retest correlation of the total amount donated measured in dollars is .25; for the logtransformed amounts the test-retest correlation is .44. For donations to organizations other than religion the test-retest correlation of the dollar amounts is .29; for the log-transformed amounts it is .39.

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Volunteering. The questions on volunteering in M1 and M2 asked about four types of formal volunteer work: ‘hospital, nursing home, or other health care-oriented work’, ‘school or other youth-related volunteer work’, ‘volunteer work for political organizations or causes’, and ‘volunteer work for any other organization, cause or charity’. While these questions did not explicitly identify religious organizations, respondents could report volunteering for religious organizations in the question about any ‘other’ organizations. A separate variable was created excluding potentially religious volunteering by computing the sum of hours volunteered in the first three types. The test-retest correlation of the total number of volunteer hours is .38; for the log-transformed hours the test-retest correlation is .46. For the hours volunteered in organizations other than religious organizations the test-retest correlation is .28; for the log-transformed variable it is .36.

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